Novel PET/CT image fusion via Gram-Schmidt spectral sharpening

Ronald T. Kneusel; Peter N. Kneusel

doi:10.1117/12.2006622

13 March 2013 Novel PET/CT image fusion via Gram-Schmidt spectral sharpening

Ronald T. Kneusel, Peter N. Kneusel

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86692Y (2013) https://doi.org/10.1117/12.2006622
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

PET/CT is a widely used dual-modality imaging technique that has been clearly shown to improve tumor localization and hence patient outcomes. The standard means by which PET/CT images are displayed for review is alpha-blending which results in a merge of the two images using a variable parameter, α, to select the relative proportion of each image displayed. In this work, we present a new fusion technique based on Gram- Schmidt spectral sharpening to display the physiological information found in the PET image along with the anatomical details from the higher resolution CT image. A selected color table is applied to the PET data to create a mult-channel (multiband) RGB image. This image, up-scaled to the resolution of the CT data, along with the original PET data which represents a lower resolution single-channel (panchromatic) image, is processed via Gram-Schmidt orthogonalization. Then, the higher resolution CT data, modified to more closely match the PET statistics, is substituted for the first vector of the new orthogonal set. Finally, an inverse Gram-Schmidt process restores the data and results in a new RGB image which is the fusion of the original PET/CT data. We show that this new image provides a clear indication of PET activity while preserving the details of the CT image. We compare these images with alpha-blended images as well as color-based and PCA-based spectral sharpening results.

Citation Download Citation

Ronald T. Kneusel and Peter N. Kneusel "Novel PET/CT image fusion via Gram-Schmidt spectral sharpening", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86692Y (13 March 2013); https://doi.org/10.1117/12.2006622

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